The search of sphericity evaluation is a time-consuming work. The minimum circumscribed sphere (MCS) is suitable for the sphere with the maximum material condition. An algorithm of sphericity evaluation based on the MCS is introduced. The MCS of a measured data point set is determined by a small number of critical data points according to geometric criteria. The vertices of the convex hull are the candidates of these critical data points. Two theorems are developed to solve the sphericity evaluation problems. The validated results show that the proposed strategy offers an effective way to identify the critical data points at the early stage of computation and gives an efficient approach to solve the sphericity problems.
Among the four methods (minimum zone sphere, minimum circumscribed sphere, maximum inscribed sphere, and least square sphere), only the minimum zone sphere complies with ANSI and ISO standards and has the minimum sphericity error value. Evaluation of sphericity error is formulated as a non-differentiable unconstrained optimization problem and hard to handle. The minimum circumscribed sphere and the maximum inscribed sphere are all easily solved by iterative comparisons, so the relationship between the minimum zone sphere and the minimum circumscribed sphere, the maximum inscribed sphere is proposed to solve efficiently the minimum zone problem. The relationship is implemented and validated with the data available in the literature.
Snow related failures can have significant impact on the safety of people who occupy snow damaged buildings. So the research for snow distribution characteristics on the roofs can avoid personnel casualty and economic losses caused by heavy snowdrift. This paper outlines the current researches of snow distribution on surface of the different roofs and the methods of researching for snowdrifting. The practical calculation method of the snow load on the typical low rise buildings was investigated by comparison between the different countries load code for example China, America, Canada and Europe.
Because of different types of load, material properties deviation and construction errors, structures have initial defects inevitably. Therefore structural damages emerge easily and have strong randomness. At the same time, the ideal design model often has difference with structure in service. To most structures, the initial testing dates cannot be obtained, while this initial model is very important to structural damage detection. So the ideal model needs to revise. In this paper, elastic modulus, Poisson ratio and link section area are given as initial random defects and these defects obey normal distribution which can be constructed by Monte Carlo probabilistic design method. Firstly, the sensitivity parameters to structural response will be received by PDS technology from Ansys. Next, the square pyramid space grid models with random defects were obtained. Finally, given link element damage, using the method combined curvature mode difference with wavelet transform, the link element damage can be determined. Through analysis, the effects about the initial defects to damage detection will be obtained.
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